Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2022
Forfattere
Saheba Bhatnagar Stefano Puliti Bruce Talbot Joachim Bernd Heppelmann Johannes Breidenbach Rasmus AstrupSammendrag
Wheel ruts, i.e. soil deformations caused by harvesting machines, are considered a negative environmental impact of forest operations and should be avoided or ameliorated. However, the mapping of wheel ruts that would be required to monitor harvesting operations and to plan amelioration measures is a tedious and time-consuming task. Here, we examined whether a combination of drone imagery and algorithms from the field of artificial intelligence can automate the mapping of wheel ruts. We used a deep-learning image-segmentation method (ResNet50 + UNet architecture) that was trained on drone imagery acquired shortly after harvests in Norway, where more than 160 km of wheel ruts were manually digitized. The cross-validation of the model based on 20 harvested sites resulted in F1 scores of 0.69–0.84 with an average of 0.77, and in total, 79 per cent of wheel ruts were correctly detected. The highest accuracy was obtained for severe wheel ruts (average user’s accuracy (UA) = 76 per cent), and the lowest accuracy was obtained for light wheel ruts (average UA = 67 per cent). Considering the nowadays ubiquitous availability of drones, the approach presented in our study has the potential to greatly increase the ability to effectively map and monitor the environmental impact of final felling operations with respect to wheel ruts. The automated mapping of wheel ruts may serve as an important input to soil impact analyses and thereby support measures to restore soil damages.
Forfattere
Trond MæhlumSammendrag
Det er ikke registrert sammendrag
Forfattere
Frode VeggelandSammendrag
Det er ikke registrert sammendrag
Sammendrag
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Forfattere
Nicolai MunsterhjelmSammendrag
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Forfattere
Nicolai MunsterhjelmSammendrag
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Forfattere
Nicolai MunsterhjelmSammendrag
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Forfattere
Bart Immerzeel Jan Vermaat Dennis Collentine Artti Juutinen Brian Kronvang Eva Skarbøvik Mette CarstensenSammendrag
Det er ikke registrert sammendrag
Forfattere
Heidi Udnes Aamot Simeon Rossmann Erik Lysøe Guro Brodal Birgitte Henriksen Ruth Dill-Macky Carl Gunnar Fossdal Ingerd Skow HofgaardSammendrag
We used metabarcoding of ITS 1 and 2 to compare the mycobiome of Norwegian spring wheat seed lots of two commonly grown spring wheat varieties (Mirakel and Zebra) harvested in 2016 and 2017. The seed lots varied in germination and were grouped according to high and low germination (≥90% and <90% germinated seeds, respectively) determined by the ISTA germination method. In addition, the percentage of each seed lot infested by the most important wheat pathogens (Microdochium spp., Fusarium spp., and Parastagonospora nodorum) was determined using a plate-out test on PDA, and species-specific qPCR was used to quantify the amount of DNA of F. avenaceum, F. culmorum, F. graminearum, F. poae, M. majus, M. nivale, and P. nodorum. Our study indicated that the presence of Microdochium was most associated with poor germination (which is as expected), while P. nodorum; although present at relatively high levels, apparently had limited impact on germination. Among the species quantified by qPCR, M. majus was the most abundant, F. avenaceum was detected at low levels, whereas the other fusaria were barely detected. Metabarcoding data indicated a negative association between the presence of the fungal genus Neoascochyta and germination, while Pyrenophora and Alternaria species appeared positively associated with germination. Our results indicated some co-existence patterns between fungal species, including both pathogenic and non-pathogenic species, with some species combinations associated with the germination potential of wheat seed.
Forfattere
Heidi Udnes AamotSammendrag
Det er ikke registrert sammendrag